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This paper presents a simple control strategy for the operation of a variable speed stand-alone wind turbine with a permanent magnet synchronous generator (PMSG). The PMSG is connected to a three phase resistive load through a switch mode rectifier and a voltage source inverter. Control of the generator side converter is used to achieve maximum power extraction from the available wind power. Control of the DC-DC bidirectional buck-boost converter, which is connected between batteries bank and DC-link voltage, is used to maintain the DC-link voltage at a constant value. It is also used to make the batteries bank stores the surplus of wind energy and supplies this energy to the load during a wind power shortage. The load side voltage source inverter uses a relatively complex vector control scheme to control the output load voltage in terms of amplitude and frequency. The control strategy works under wind speed variation as well as with variable load. Extensive simulation results have been performed using MATLAB/SIMULINK.

The precision of the PV model greatly influences the simulation results to enhance the effectiveness of photovoltaic (PV) energy systems. The PV mathematical model is based on a remarkably nonlinear relationship of its I-V characteristic. The data sheets of overall PV cells do not supply complete information of its parameters. This leads to a nonlinear mathematical model of PV with numerous unknown parameters. Consequently, in this paper, a new application of an appropriate optimization algorithm called Chaos Game Optimization algorithm (CGO) is proposed for estimating the unknown parameters of the threediode (TD) PV model. The simulation results are carried out for PV real cells and PV module which with varying the temperature and irradiation. The proposed model of the PV module is evaluated by matching its results with the actual PV modules experimental results. To confirm the performance of the CGO algorithm in extracting the parameters of the PV model, its results are compared with the most present and robust techniques results in the literature. The results show that the CGO algorithm attains the least Root Mean Square Error (RMSE), the mean and standard deviation as the best solution. In addition, CGO provides the smallest implementation time compared with the other investigated algorithms.INDEX TERMS Chaos game optimization algorithm, optimization, PV parameter estimation, three-diode model.

This paper presented both the linear quadratic Gaussian technique (LQG) and the coefficient diagram method (CDM) as load frequency controllers in a multi-area power system to deal with the problem of variations in system parameters and load demand change. The full states of the system including the area frequency deviation have been estimated using the Kalman filter technique. The efficiency of the proposed control method has been checked using a digital simulation. Simulation results indicated that, with the proposed CDM + LQG technique, the system is robust in the face of parameter uncertainties and load disturbances. A comparison between the proposed technique and other schemes is carried out, confirming the superiority of the proposed CDM + LQG technique.

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